in hospitalized patients to prevent the spread of SARS-CoV-2 infections.
We show that a pragmatic model can predict which patients should be retested for COVID. Further research is required to determine if this risk model can be applied prospectively in hospitalized patients to prevent the spread of SARS-CoV-2 infections.Wastewater-based epidemiology is an emerging tool to monitor COVID-19 infection levels by measuring the concentration of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater. There remains a need to improve wastewater RNA extraction methods' sensitivity, speed, and reduce reliance on often expensive commercial reagents to make wastewater-based epidemiology more accessible. We present a kit-free wastewater RNA extraction method, titled "Sewage, Salt, Silica and SARS-CoV-2" (4S), that employs the abundant and affordable reagents sodium chloride (NaCl), ethanol and silica RNA capture matrices to recover 6-fold more SARS-CoV-2 RNA from wastewater than an existing ultrafiltration-based method. https://www.selleckchem.com/products/shin1-rz-2994.html The 4S method concurrently recovered pepper mild mottle virus (PMMoV) and human 18S ribosomal subunit rRNA, both suitable as fecal concentration controls. The SARS-CoV-2 RNA concentrations measured in three sewersheds corresponded to the relative prevalence of COVID-19 infection determined via clinical testing. Lastly, controlled experiments indicate that the 4S method prevented RNA degradation during storage of wastewater samples, was compatible with heat pasteurization, and could be performed in approximately 3 hours. Overall, the 4S method is promising for effective, economical, and accessible wastewater-based epidemiology for SARS-CoV-2, providing another tool to fight the global pandemic.The 4S method for measuring SARS-CoV-2 in wastewater is promising for effective, economical, and accessible wastewater-based epidemiology.
Racial and ethnic disparities in COVID-19 outcomes reflect the unequal burden experienced by vulnerable communities in the United States (US). Proposed explanations include socioeconomic factors that influence how people live, work, and play, and pre-existing comorbidities. It is important to assess the extent to which observed US COVID-19 racial and ethnic disparities can be explained by these factors. We study 9.8 million confirmed cases and 234,000 confirmed deaths from 2,990 US counties (3,142 total) that make up 99.8% of the total US population (327.6 out of 328.2 million people) through 11/8/20. We found national COVID-19 racial health disparities in US are partially explained by various social determinants of health and pre-existing comorbidities that have been previously proposed. However, significant unexplained racial and ethnic health disparities still persist at the US county level after adjusting for these variables. There is a pressing need to develop strategies to address not only the social determinants but also other factors, such as testing access, personal protection equipment access and exposures, as well as tailored intervention and resource allocation for vulnerable groups, in order to combat COVID-19 and reduce racial health disparities.Retrospective study of COVID-19 positive patients treated at NYU Langone Health (NYULH) to identify clinical markers predictive of disease severity to assist in clinical decision triage and provide additional biological insights into disease progression.
Clinical activity of 3740 de-identified patients at NYULH between January and August 2020. Models were trained on clinical data during different parts of their hospital stay to predict three clinical outcomes deceased, ventilated, or admitted to ICU.
XGBoost model trained on clinical data from the final 24 hours excelled at predicting mortality (AUC=0.92, specificity=86% and sensitivity=85%). Respiration rate was the most important feature, followed by SpO2 and age 75+. Performance of this model to predict the deceased outcome extended 5 days prior with AUC=0.81, specificity=70%, sensitivity=75%. When only using clinical data from the first 24 hours, AUCs of 0.79, 0.80, and 0.77 were obtained for deceased, ventilated, or ICU admitted, respectively. Although respiration rate and SpO2 levels offered the highest feature importance, other canonical markers including diabetic history, age and temperature offered minimal gain. When lab values were incorporated, prediction of mortality benefited the most from blood urea nitrogen (BUN) and lactate dehydrogenase (LDH). Features predictive of morbidity included LDH, calcium, glucose, and C-reactive protein (CRP).
Together this work summarizes efforts to systematically examine the importance of a wide range of features across different endpoint outcomes and at different hospitalization time points.
Together this work summarizes efforts to systematically examine the importance of a wide range of features across different endpoint outcomes and at different hospitalization time points.Convalescent plasma with severe acute respiratory disease coronavirus 2 (SARS-CoV-2) antibodies (CCP) may hold promise as treatment for Coronavirus Disease 2019 (COVID-19). We compared the mortality and clinical outcome of patients with COVID-19 who received 200mL of CCP with a Spike protein IgG titer ?12,430 (median 147,385) within 72 hours of admission to propensity score-matched controls cared for at a medical center in the Bronx, between April 13 to May 4, 2020. Matching criteria for controls were age, sex, body mass index, race, ethnicity, comorbidities, week of admission, oxygen requirement, D-dimer, lymphocyte counts, corticosteroids, and anticoagulation use. There was no difference in mortality or oxygenation between CCP recipients and controls at day 28. When stratified by age, compared to matched controls, CCP recipients less then 65 years had 4-fold lower mortality and 4-fold lower deterioration in oxygenation or mortality at day 28. For CCP recipients, pre-transfusion Spike protein IgG, IgM and IgA titers were associated with mortality at day 28 in univariate analyses. No adverse effects of CCP were observed. Our results suggest CCP may be beneficial for hospitalized patients less then 65 years, but data from controlled trials is needed to validate this finding and establish the effect of ageing on CCP efficacy.